V. Filimonov

发表

Power Law Scaling and 'Dragon-Kings' in Distributions of Intraday Financial Drawdowns

D. Sornette, V. Filimonov, 2014, 1407.5037.

Self-excited multifractal dynamics

D. Sornette, V. Filimonov, 2010, 1008.1430.

A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model

D. Sornette, V. Filimonov, 2011, 1108.0099.

A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model

D. Sornette, V. Filimonov, 2011, 1108.0099.

Quantifying Reflexivity in Financial Markets: Towards a Prediction of Flash Crashes

D. Sornette, V. Filimonov, 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

Quantifying reflexivity in financial markets: towards a prediction of flash crashes

D. Sornette, V. Filimonov, 2012, 1201.3572.

Power Law Scaling and 'Dragon-Kings' in Distributions of Intraday Financial Drawdowns

D. Sornette, V. Filimonov, 2014 .

Detection of intensity bursts using Hawkes processes: An application to high-frequency financial data.

F. Lillo, V. Filimonov, M. Rambaldi, 2016, Physical Review E.

Modified profile likelihood inference and interval forecast of the burst of financial bubbles

D. Sornette, V. Filimonov, G. Demos, 2017 .

Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data

Didier Sornette, Vladimir Filimonov, D. Sornette, 2013, 1308.6756.

Bridge homogeneous volatility estimators

D. Sornette, V. Filimonov, A. Saichev, 2014 .

Modified profile likelihood inference and interval forecast of the burst of financial bubbles

Didier Sornette, Vladimir Filimonov, Guilherme Demos, 2016, 1602.08258.

On the Modeling of Financial Time Series

Vladimir Filimonov, Aleksey Kutergin, V. Filimonov, 2015 .

Quantification of the High Level of Endogeneity and of Structural Regime Shifts in Commodity Markets

Didier Sornette, Vladimir Filimonov, David Bicchetti, 2013 .

Real-Time Prediction and Post-Mortem Analysis of the Shanghai 2015 Stock Market Bubble and Crash

Didier Sornette, Peter Cauwels, Vladimir Filimonov, 2015 .

The Hawkes process with renewal immigration & its estimation with an EM algorithm

Didier Sornette, Spencer Wheatley, Vladimir Filimonov, 2016, Comput. Stat. Data Anal..

Estimation of the Hawkes Process with Renewal Immigration Using the EM Algorithm

Didier Sornette, Spencer Wheatley, Vladimir Filimonov, 2014, 1407.7118.

Effective measure of endogeneity for the Autoregressive Conditional Duration point processes via mapping to the self-excited Hawkes process

Didier Sornette, Spencer Wheatley, Vladimir Filimonov, 2013, Commun. Nonlinear Sci. Numer. Simul..

Forecasting Intensity of Mid-Quote Price Changes Via the Hawkes Model

Vladimir Filimonov, Joel Bloch, V. Filimonov, 2014 .

Numerical simulation of quasi-multifractal diffusion process

V. Filimonov, A. Saichev, 2008 .

Numerical simulation of the realizations and spectra of a quasi-multifractal diffusion process

V. Filimonov, A. Saichev, 2008 .

On the spectrum of multifractal diffusion process

V. Filimonov, A. Saichev, 2007 .

Homogeneous Volatility Bridge Estimators

D. Sornette, V. Filimonov, A. Saichev, 2009, 0912.1617.

Most Efficient Homogeneous Volatility Estimators

D. Sornette, V. Filimonov, A. Saichev, 2009, 0908.1677.

Views to a war: systematic differences in media and military reporting of the war in Iraq

Vladimir Filimonov, Karsten Donnay, V. Filimonov, 2014, EPJ Data Science.